{"id":"https://openalex.org/W2756957295","doi":"https://doi.org/10.1109/access.2017.2754327","title":"Sparse-Prior-Based Projection Distance Optimization Method for Joint CT-MRI Reconstruction","display_name":"Sparse-Prior-Based Projection Distance Optimization Method for Joint CT-MRI Reconstruction","publication_year":2017,"publication_date":"2017-01-01","ids":{"openalex":"https://openalex.org/W2756957295","doi":"https://doi.org/10.1109/access.2017.2754327","mag":"2756957295"},"language":"en","primary_location":{"id":"doi:10.1109/access.2017.2754327","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2017.2754327","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2017.2754327","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5075862602","display_name":"Xuelin Cui","orcid":"https://orcid.org/0000-0003-2256-2293"},"institutions":[{"id":"https://openalex.org/I859038795","display_name":"Virginia Tech","ror":"https://ror.org/02smfhw86","country_code":"US","type":"education","lineage":["https://openalex.org/I859038795"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Xuelin Cui","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Virginia Tech, Falls Church, VA, USA"],"raw_orcid":"https://orcid.org/0000-0003-2256-2293","affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Virginia Tech, Falls Church, VA, USA","institution_ids":["https://openalex.org/I859038795"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073678278","display_name":"Lamine Mili","orcid":"https://orcid.org/0000-0001-6134-3945"},"institutions":[{"id":"https://openalex.org/I859038795","display_name":"Virginia Tech","ror":"https://ror.org/02smfhw86","country_code":"US","type":"education","lineage":["https://openalex.org/I859038795"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Lamine Mili","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Virginia Tech, Falls Church, VA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Virginia Tech, Falls Church, VA, USA","institution_ids":["https://openalex.org/I859038795"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5052662150","display_name":"Hengyong Yu","orcid":"https://orcid.org/0000-0002-5852-0813"},"institutions":[{"id":"https://openalex.org/I133738476","display_name":"University of Massachusetts Lowell","ror":"https://ror.org/03hamhx47","country_code":"US","type":"education","lineage":["https://openalex.org/I133738476"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hengyong Yu","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Massachusetts Lowell, Lowell, MA, USA"],"raw_orcid":"https://orcid.org/0000-0002-5852-0813","affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Massachusetts Lowell, Lowell, MA, USA","institution_ids":["https://openalex.org/I133738476"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5075862602"],"corresponding_institution_ids":["https://openalex.org/I859038795"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":1.9735,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.86102973,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"5","issue":null,"first_page":"20099","last_page":"20110"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10378","display_name":"Advanced MRI Techniques and Applications","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T10378","display_name":"Advanced MRI Techniques and Applications","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10522","display_name":"Medical Imaging Techniques and Applications","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/iterative-reconstruction","display_name":"Iterative reconstruction","score":0.7437683939933777},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7197571396827698},{"id":"https://openalex.org/keywords/real-time-mri","display_name":"Real-time MRI","score":0.6852597594261169},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5995645523071289},{"id":"https://openalex.org/keywords/compressed-sensing","display_name":"Compressed sensing","score":0.5879359245300293},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5036842226982117},{"id":"https://openalex.org/keywords/image-quality","display_name":"Image quality","score":0.47900885343551636},{"id":"https://openalex.org/keywords/projection","display_name":"Projection (relational algebra)","score":0.4658340811729431},{"id":"https://openalex.org/keywords/medical-imaging","display_name":"Medical imaging","score":0.45406150817871094},{"id":"https://openalex.org/keywords/joint","display_name":"Joint (building)","score":0.43862104415893555},{"id":"https://openalex.org/keywords/magnetic-resonance-imaging","display_name":"Magnetic resonance imaging","score":0.4227459728717804},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.33192771673202515},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.2779248058795929},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.2271137535572052},{"id":"https://openalex.org/keywords/radiology","display_name":"Radiology","score":0.11769822239875793}],"concepts":[{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.7437683939933777},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7197571396827698},{"id":"https://openalex.org/C157787499","wikidata":"https://www.wikidata.org/wiki/Q13479657","display_name":"Real-time MRI","level":3,"score":0.6852597594261169},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5995645523071289},{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.5879359245300293},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5036842226982117},{"id":"https://openalex.org/C55020928","wikidata":"https://www.wikidata.org/wiki/Q3813865","display_name":"Image quality","level":3,"score":0.47900885343551636},{"id":"https://openalex.org/C57493831","wikidata":"https://www.wikidata.org/wiki/Q3134666","display_name":"Projection (relational algebra)","level":2,"score":0.4658340811729431},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.45406150817871094},{"id":"https://openalex.org/C18555067","wikidata":"https://www.wikidata.org/wiki/Q8375051","display_name":"Joint (building)","level":2,"score":0.43862104415893555},{"id":"https://openalex.org/C143409427","wikidata":"https://www.wikidata.org/wiki/Q161238","display_name":"Magnetic resonance imaging","level":2,"score":0.4227459728717804},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.33192771673202515},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2779248058795929},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2271137535572052},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.11769822239875793},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C170154142","wikidata":"https://www.wikidata.org/wiki/Q150737","display_name":"Architectural engineering","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/access.2017.2754327","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2017.2754327","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:843953a6d2164c67a4f6a9bd05dff048","is_oa":true,"landing_page_url":"https://doaj.org/article/843953a6d2164c67a4f6a9bd05dff048","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 5, Pp 20099-20110 (2017)","raw_type":"article"},{"id":"pmh:oai:vtechworks.lib.vt.edu:10919/89527","is_oa":true,"landing_page_url":"http://hdl.handle.net/10919/89527","pdf_url":null,"source":{"id":"https://openalex.org/S4306400248","display_name":"VTechWorks (Virginia Tech)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I859038795","host_organization_name":"Virginia Tech","host_organization_lineage":["https://openalex.org/I859038795"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Text"}],"best_oa_location":{"id":"doi:10.1109/access.2017.2754327","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2017.2754327","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9","score":0.4000000059604645}],"awards":[{"id":"https://openalex.org/G8239341598","display_name":null,"funder_award_id":"1540898","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":44,"referenced_works":["https://openalex.org/W569855300","https://openalex.org/W1924463094","https://openalex.org/W1961774439","https://openalex.org/W1972150100","https://openalex.org/W1976784524","https://openalex.org/W1988849934","https://openalex.org/W2000993829","https://openalex.org/W2002664473","https://openalex.org/W2012231377","https://openalex.org/W2012960907","https://openalex.org/W2014823423","https://openalex.org/W2015738893","https://openalex.org/W2029738926","https://openalex.org/W2029816571","https://openalex.org/W2037521346","https://openalex.org/W2050267082","https://openalex.org/W2053141865","https://openalex.org/W2055269346","https://openalex.org/W2069878070","https://openalex.org/W2116670064","https://openalex.org/W2130645492","https://openalex.org/W2133665775","https://openalex.org/W2145096794","https://openalex.org/W2146029121","https://openalex.org/W2149400409","https://openalex.org/W2156994346","https://openalex.org/W2164452299","https://openalex.org/W2165565866","https://openalex.org/W2167122131","https://openalex.org/W2167150277","https://openalex.org/W2296616510","https://openalex.org/W2327492324","https://openalex.org/W2344831632","https://openalex.org/W2347124429","https://openalex.org/W2559980017","https://openalex.org/W3014839492","https://openalex.org/W3098053367","https://openalex.org/W3101510409","https://openalex.org/W3116297301","https://openalex.org/W4233622498","https://openalex.org/W4237938455","https://openalex.org/W4250955649","https://openalex.org/W4293775970","https://openalex.org/W6650994880"],"related_works":["https://openalex.org/W2896778670","https://openalex.org/W2757389719","https://openalex.org/W2951714568","https://openalex.org/W2339684922","https://openalex.org/W1979782214","https://openalex.org/W1963814553","https://openalex.org/W2037595954","https://openalex.org/W1988158806","https://openalex.org/W2507293823","https://openalex.org/W2386146599"],"abstract_inverted_index":{"Multimodal":[0],"imaging":[1,17,34,102],"techniques":[2,165],"have":[3],"received":[4],"a":[5,22,52,168,177,197,242],"great":[6],"deal":[7],"of":[8,91,106,180,190,199,227,258,284],"attention,":[9],"since":[10],"their":[11],"inceptions":[12],"for":[13,27],"achieving":[14],"an":[15,89,218],"enhanced":[16],"performance.":[18],"In":[19],"this":[20,78],"paper,":[21],"novel":[23],"joint":[24,239,285],"reconstruction":[25,154,240,252],"framework":[26,158],"computed":[28],"tomography":[29],"(CT)":[30],"and":[31,38,42,49,126,148,203,211,221,250,269],"magnetic":[32],"resonance":[33],"(MRI)":[35],"is":[36,109,159,194,263],"implemented":[37,166],"evaluated.":[39],"The":[40,139,156,188],"CT":[41,125,147,202,210],"MRI":[43,127,149,204,212],"data":[44,59],"sets":[45,60],"are":[46,61,70,129,214,277],"synchronously":[47],"acquired":[48],"registered":[50],"from":[51,88,118,136,274],"hybrid":[53],"CT-MRI":[54],"platform.":[55],"Because":[56],"the":[57,64,82,96,104,113,122,133,142,146,162,181,191,209,237,255,259,266,282],"image":[58,244,286],"highly":[62],"undersampled,":[63],"conventional":[65],"methods":[66,223,249],"(e.g.,":[67],"analytic":[68,219,248],"reconstructions)":[69],"unable":[71],"to":[72,99,111,151,186,279],"generate":[73],"decent":[74],"results.":[75],"To":[76],"overcome":[77],"drawback,":[79],"we":[80],"employ":[81],"compressed":[83],"sensing":[84],"(CS)":[85],"sparse":[86],"priors":[87],"application":[90],"discrete":[92],"gradient":[93],"transform.":[94],"On":[95],"other":[97],"hand,":[98],"utilize":[100],"multimodal":[101],"information,":[103],"concept":[105],"projection":[107],"distance":[108],"introduced":[110],"penalize":[112],"large":[114],"divergence":[115],"between":[116,145],"images":[117,128,150,213,273],"different":[119,275],"modalities.":[120],"During":[121],"optimization":[123],"process,":[124],"alternately":[130],"updated":[131],"using":[132],"latest":[134],"information":[135],"current":[137],"iteration.":[138],"method":[140],"exploits":[141],"structural":[143,228,267],"similarities":[144,268],"achieve":[152],"better":[153,243],"quality.":[155],"entire":[157],"accelerated":[160],"via":[161],"parallel":[163],"processing":[164],"on":[167,196],"nVidia":[169],"M5000M":[170],"Graph":[171],"Processing":[172],"Unit.":[173],"This":[174],"results":[175],"in":[176,272],"significant":[178],"decrease":[179],"computational":[182],"time":[183],"(from":[184],"hours":[185],"minutes).":[187],"performance":[189],"proposed":[192,238],"approach":[193],"demonstrated":[195],"pair":[198],"undersampled":[200],"projections":[201],"body":[205],"images.":[206,261],"For":[207],"comparison,":[208],"also":[215],"reconstructed":[216],"by":[217,253],"method,":[220],"iterative":[222],"with":[224],"no":[225],"exploration":[226],"similarity,":[229],"known":[230],"as":[231],"independent":[232,251],"reconstructions.":[233],"Results":[234],"show":[235],"that":[236,265],"provides":[241],"quality":[245,283],"than":[246],"both":[247],"revealing":[254],"main":[256],"features":[257],"true":[260],"It":[262],"concluded":[264],"correlations":[270],"residing":[271],"modalities":[276],"useful":[278],"mutually":[280],"promote":[281],"reconstruction.":[287]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":5}],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2025-10-10T00:00:00"}
